Numerous platforms and solutions are known for finding and filtering content for users, however, these generally have not been developed with the intent of finding content to share.
Sharing content builds relationships. When one person (a user) shares highly relevant content with another person (a consumer) the user is performing a service for the consumer. This service saves the consumer time and effort that would have been spent searching for relevant content. It may also provide information to the consumer that they would not have otherwise seen.
Sharing content can also reduce discovery time, which may be valuable specially for time-sensitive information. Also, finding relevant content for a consumer requires a deep knowledge of them, for example their interests, likes and dislikes, current challenges, and history. Sharing this content demonstrates to the consumer that the user cares about their relationship with the consumer. The user also expressly demonstrates that the user is actively thinking about the consumer and their relationship.
Relationship managers understand the value of sharing content but their challenge is sometimes is that relevant content is not easily found. The common approach to finding relevant content is to monitor specific channels of interest from a specific source, for example reading the technology section of the New York Times™ or the Mashable™ blog. Although this approach generally assures good quality content, relevance is unpredictable because the category (for example “technology”) is generally too broad. The approach must be more targeted to be efficient in finding highly relevant content for others.
Developments in the field by news aggregators (Alltop.com™, Google News™, Feed.ly™, Prismatic™) or search services (Google Alerts™) have increased relevance by expanding the sources and narrowing categories to topics or keywords. Instead of browsing through technology articles from a single source, it is now possible to select the relevant topics in “technology”, for example “mobile applications” or “enterprise security” across multiple sources. The problem with these services is that they are designed to present a high volume of current, topically relevant items and to do that they must sacrifice specificity. Instead of finding one article that meets all of the topics of interest and that is therefore highly relevant, the prior art platforms or tools will generally find many for each topic articles that are relevant for the topic but that may or may not be relevant to a set of interests.
Additionally, effort is needed to select the topic feeds or enter the keywords to monitor. This is worthwhile when mining content for oneself but does not scale to mining content for several relationships that a user may be managing. Also, when executing relationship management tasks, streams of information are required rather than on-demand search services. For example a salesperson may need to contact a client about a new service and needs a news article to engage them immediately.
Web search can be used to find articles of interest on demand but the most common search engines (Google Search™, Microsoft Bing™) are built for general utility and they are limited in serving this specific need. Queries generally must be manually developed by reviewing known information about the contact and determining which keywords to use and how to structure the query to return articles that are specifically relevant to the interest set of the contact. This is not a trivial task and cab exceed the search expertise of most users.
Content is not limited to news articles and other traditional web documents. The rise of social media presents a new search challenge and opportunity. Finding people for introductions, new sales leads, or to fill jobs, is now possible at scale and with a high degree of precision. The challenge is very similar to other content types—how does one mine all of that content (profiles, publications, network relationships) efficiently.
The present invention has been developed with a view to the foregoing considerations.